Distributed computing applications are often deployed into environments having a multitude of different technologies and services that are used to form building blocks of the applications. Examples of distributed applications are legion and can include enterprise applications such as line of business or LOB, billing systems, customer relationship management or CRM, enterprise resource planning or ERP, business intelligence, human resource management, manufacturing, inventory control applications, and others. Such applications include components that are typically distributed across tiers in a computer network. Also, some applications are intended to run in a cloud computing environment, others are intended to run on the premises of the entity or user, and others are intended to span these environments. Further, the environment may change as an application evolves, the number of users change, or the locations of the users become dispersed.
One desirable characteristic of a distributed application is its ability to scale, or to cost-effectively change with the enterprise. Existing program models do not aim to support the development of scalable distributed applications. Typical component models are designed for desktop applications and are tier and technology specific. A distributed application is typically comprised of a set of distinct components, spread across tiers, which interact to perform work. While the components are virtualized, the relationship between the components is not. A physical wiring of components during runtime interaction is typically statically determined or otherwise hard-coded in this framework, which can place limits on the ways in which the application can be scaled or even on the application's overall ability to scale. While working with such models, many developers try to avoid writing stateful components because they are difficult to scale, but in making this choice the developer sacrifices benefits of other approaches, such as the natural expression of application logic.
Current techniques of state portioning and replication are limited to high-end developers and are implemented by technologies of databases and distributed caches. There is no program model, however, that makes these techniques and technologies approachable and mainstream for developers to use in writing and scaling application state logic.